Ideotype breeding for crop adaptation to low phosphorus availability on extensive organic farms

Organic farming in extensive production regions, such as the Canadian prairies have a particularly difficult challenge of replenishing soil reserves of phosphorus (P). Organic grains are exported off the farm while resupply of lost P is difficult due to limited availability of animal manures and low solubility of rock organic fertilizers. As a result, many organic farms on the prairies are deficient in plant-available P, leading to productivity breakdown. A portion of the solution may involve crop genetic improvement. A hypothetical 'catch and release' wheat ideotype for organic production systems is proposed to (i) enhance P uptake and use efficiency but (ii) translocate less P from the vegetative biomass into the grain. Root traits that would improve P uptake efficiency from less-available P pools under organic production are explored. The need to understand and classify 'phosphorus use efficiency' using appropriate indices for organic production is considered, as well as the appropriate efficiency indices for use if genetically selecting for the proposed ideotype. The implications for low seed P and high vegetative P are considered from a crop physiology, environmental, and human nutrition standpoint; considerations that are imperative for future feasibility of the ideotype.

Identification of agro-physiological traits of lentil that reduce risks of drought

Ideotype breeding is an essential approach for selection of desired combination of plant traits for testing in crop growth model for potential yield gain in specific environments and management practices. Here we parameterized plant traits for untested lentil cultivars for the APSIM-lentil model in phenology, biomass, and seed yield. We then tested these against independent data and applied the model in an extrapolated analysis (i) to assess the impact of drought on productivity across different rainfall environments; (ii) to identify impactful plant traits and (iii) to design new lentil ideotypes with a combination of desirable traits that mitigate the impact of drought, in the context of various agronomic practices across a wide range of production environments. Desirable phenological and physiological traits related to yield were identified with RUE having the greatest effect on yield followed by HI rate. Leaf size significantly affected seed yield (p< 0.05) more than phenological phases. The physiological traits were integrated into four ideotype designs applied to two baseline cultivars (PBA Hallmark XT and PBA Jumbo2) providing eight ideotypes. We identified a combination of genetic traits that promises a yield advantage of around 10% against our current cultivars PBA Hallmark XT and PBA Jumbo2. Under drought conditions, our ideotypes achieved 5 to 25% yield advantages without stubble and 20 to 40% yield advantages with stubble residues. This shows the importance of genetic screening under realistic production conditions (e.g., stubble retention in particular environments). Such screening is aided by the employment of biophysical models that incorporate both genetic and agronomic variables that focus on successful traits in combination, to reduce the impact of drought in the development of new cultivars for various environments. Stubble retention was found to be a major agronomic contributor to high yield in water-limiting environments and this contribution declined with increasing growing season rainfall. In mid- and high-rainfall environments, the key drivers of yield were time of sowing, physiological traits and soil type. Overall, the agronomic practices, namely, early sowing, residue retention and narrow row spacing deceased the impact of drought when combined with improved physiological traits of the ideotypes based on long term climate data.

Major QTLs, qARO1 and qARO9, Additively Regulate Adaxial Leaf Rolling in Rice

Moderate leaf rolling is considered optimal for the ideal plant type in rice (Oryza sativa L.), as it improves photosynthetic efficiency and, consequently, grain yield. Determining the genetic basis of leaf rolling via the identification of quantitative trait loci (QTLs) could facilitate the development of high-yielding varieties. In this study, we identified three stable rice QTLs, qARO1, qARO5, and qARO9, which control adaxial leaf rolling in a recombinant inbred line (RIL) population derived from a cross between Tong 88-7 (T887) and Milyang 23 (M23), using high-density SNP markers. These QTLs controlled the rolling phenotype of both the flag leaf (FL) and secondary leaf (SL), and different allelic combinations of these QTLs led to a wide variation in the degree of leaf rolling. Additive gene actions of qARO1 and qARO9 on leaf rolling were observed in a backcross population. In addition, qARO1 (markers: 01id4854718 and 01asp4916781) and qARO9 (markers: 09id19650402 and 09id19740436) were successfully fine-mapped to approximately 60- and 90-kb intervals on chromosomes 1 and 9, respectively. Histological analysis of near-isogenic lines (NILs) revealed that qARO1 influences leaf thickness across the small vein, and qARO9 affects leaf thickness in the entire leaf and bulliform cell area, thus leading to adaxial leaf rolling. The results of this study advance our understanding of the genetic and molecular bases of adaxial leaf rolling, and this information can be used for the development of rice varieties with the ideal plant type.

Use of crop simulation modelling to aid ideotype design of future cereal cultivars

A major challenge of the 21st century is to achieve food supply security under a changing climate and roughly a doubling in food demand by 2050 compared to present, the majority of which needs to be met by the cereals wheat, rice, maize, and barley. Future harvests are expected to be especially threatened through increased frequency and severity of extreme events, such as heat waves and drought, that pose particular challenges to plant breeders and crop scientists. Process-based crop models developed for simulating interactions between genotype, environment, and management are widely applied to assess impacts of environmental change on crop yield potentials, phenology, water use, etc. During the last decades, crop simulation has become important for supporting plant breeding, in particular in designing ideotypes, i.e. 'model plants', for different crops and cultivation environments. In this review we (i) examine the main limitations of crop simulation modelling for supporting ideotype breeding, (ii) describe developments in cultivar traits in response to climate variations, and (iii) present examples of how crop simulation has supported evaluation and design of cereal cultivars for future conditions. An early success story for rice demonstrates the potential of crop simulation modelling for ideotype breeding. Combining conventional crop simulation with new breeding methods and genetic modelling holds promise to accelerate delivery of future cereal cultivars for different environments. Robustness of model-aided ideotype design can further be enhanced through continued improvements of simulation models to better capture effects of extremes and the use of multi-model ensembles.